The present invention relates to an image processing apparatus for processing image data, for example, obtained by taking an image of a subject and an image processing method.
There is conventionally known an identifying device for performing individual identifying processing, for example, by using image data obtained by taking a picture of a living body (subject) (refer to, for example, the Japanese Unexamined Patent Publication No. 10-127609).
In the above conventional identifying device, identifying processing is performed, for example, by taking a picture of transmitted light of a hand of the subject and generating binarized image data based on a predetermined threshold value of pixel values of the image data. For example, the identifying device performs identifying processing based on a pattern indicating an arrangement of blood vessels in the binarized image data.
A distribution of pixel values of taken image data differs in each subject. For example, as to image data of a subject with much fat component, the distribution data of pixel values spreads in a wide range and an average value of pixel values is relatively high comparing with image data of a subject with less fat component.
Since the above conventional identifying device performs binarization processing based on a predetermined threshold value, suitable binarized image data can be generated for image data of a subject with less fat component, while there is a case where binarized data having lopsided pixel values is undesirably generated for image data of a subject with much fat component and binarization processing cannot be performed suitably, so that improvement is demanded.
Also, image data obtained by taking a picture of a subject includes very small regions equivalent to noise components, and the noise components largely affects on accuracy of identifying processing. Therefore, there has been a demand to remove regions of a predetermined size equivalent to noise components from the image data.
Also, a linear pattern in the image data is significant in the identifying processing, but the linear pattern is broken due to noise, etc. and cannot be visually recognized clearly in some cases. Therefore, there is a demand for obtaining image data including a clear linear pattern by connecting between pixel data close to each other to a certain extent by considering noise, etc.